EP4100635A2 - Verfahren zur überprüfung einer emittierten stoffmenge - Google Patents
Verfahren zur überprüfung einer emittierten stoffmengeInfo
- Publication number
- EP4100635A2 EP4100635A2 EP21701708.6A EP21701708A EP4100635A2 EP 4100635 A2 EP4100635 A2 EP 4100635A2 EP 21701708 A EP21701708 A EP 21701708A EP 4100635 A2 EP4100635 A2 EP 4100635A2
- Authority
- EP
- European Patent Office
- Prior art keywords
- data
- substance
- amount
- register
- processing device
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M15/00—Testing of engines
- G01M15/04—Testing internal-combustion engines
- G01M15/10—Testing internal-combustion engines by monitoring exhaust gases or combustion flame
- G01M15/102—Testing internal-combustion engines by monitoring exhaust gases or combustion flame by monitoring exhaust gases
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D41/1405—Neural network control
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0499—Feedforward networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1438—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor
- F02D41/1444—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases
- F02D41/146—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an NOx content or concentration
- F02D41/1461—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an NOx content or concentration of the exhaust gases emitted by the engine
- F02D41/1462—Introducing closed-loop corrections using means for determining characteristics of the combustion gases; Sensors therefor characterised by the characteristics of the combustion gases the characteristics being an NOx content or concentration of the exhaust gases emitted by the engine with determination means using an estimation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L2209/00—Additional information or applications relating to cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
- H04L2209/84—Vehicles
Definitions
- the invention relates to a method for checking an amount of substance which is emitted by the operation of a functional unit of a commercial vehicle.
- An essential criterion for commercial vehicles are emissions of specific substances during the operation of their internal combustion engine. It is of interest to be able to reliably measure and / or check the quantities or concentrations of these emitted substances.
- the present invention is based on the object of being able to check an amount of substance emitted by the operation of a functional unit of a commercial vehicle with little technical effort.
- an amount of substance is determined which is emitted by the operation of a functional unit of a commercial vehicle.
- signals from a signal source that are generated independently of the substance to be examined or the amount of substance to be determined are sent as input data to a data processing device.
- the data processing device is used to determine the amount of substance emitted, in particular by means of suitable algorithms, for example an artificial intelligence.
- the signal source is used to provide signals that are generated independently of the amount of substance. These signals therefore do not represent an amount of substance, but form input data for the data processing device.
- the latter in turn processes the input data into output data that represent the amount of substance emitted.
- the respective emitted substance can be determined technically simply and inexpensively in terms of its quantity.
- the output data of the data processing device are transferred - possibly in a further processed form - as transfer data into a memory unit of a digital distributed register (distributed ledger).
- the register enables documentation of all data transactions. This creates the prerequisite that the amount of substance emitted is reliably documented on the one hand and can be clearly checked if necessary on the other. This allows the functional unit to be reliably checked at any time to determine whether it is working within a (e.g. technically and / or legally) defined framework.
- the storage unit can be designed as a defined storage location and / or as a type of database within the register.
- the distribution properties of the register make it possible for third parties to check the functional unit with regard to the amount of substance emitted at any time (e.g. in real time or afterwards). can reliably check.
- the register can thus serve as a kind of data network.
- the distribution property of the register preferably includes a personal restriction of the participants in the register (permissioned distributed ledger). This means that only authorized third parties (e.g. with the appropriate access authorization) can carry out data transactions and / or check the functional unit with regard to the amount of substance emitted. These third parties are, for example, the user or manufacturer of the functional unit, cooperation partner or supplier of the manufacturer or institutions provided for by legislation (e.g. technical testing authority).
- the register then serves as a kind of private data network with a restricted group of participants.
- the participants in the register or their technical units or modules communicating with the register preferably have a corresponding digital certificate to identify themselves as authorized register participants.
- At least one sensor, a combination of several sensors or a control unit is preferably provided for generating and providing the signals, which are independent of the amount of substance.
- the control unit can also send signals from a control and / or data bus (e.g. CAN, ISO) and make them available as signals that are independent of the amount of substance.
- Sensor signals derived from a family of characteristics can also be provided via the control unit.
- the sensor or the sensor system can be part of a unit outside the commercial vehicle, for example satellite, drone, weather station.
- Their signals or data can then first be fed to a control unit or sent directly to the data processing device as input data.
- Data from a data network e.g. Internet
- the latter data can, if necessary, first be fed to a control unit, which then sends the relevant data as input data to the data processing unit.
- Different emission substances are conceivable as the determined amount of substance, each of which is examined or checked with regard to the amount emitted (e.g. concentration, number of particles, particle flow, volume flow).
- the specific amount of substance can be investigated or determined regardless of its physical state (solid, liquid, gaseous). Even individual substances with several states of aggregation at the same time can be checked with regard to their quantity by a correspondingly designed data processing device.
- the data processing device can be designed to examine a single substance and consequently to determine a single specific amount of substance. Alternatively, the data processing device is designed in such a way that it is suitable for examining several different specific substances.
- the utility vehicle is in particular an agricultural utility vehicle, for example a tractor or tractor. Further examples are forestry utility vehicles and construction machinery.
- the data processing device preferably contains at least one neural network as a learned model for processing the input data. Using the at least one neural network, output data are generated in the data processing device which represent the amount of substance emitted.
- the use of the data processing device with the at least one neural network enables input data to be processed reliably with high accuracy on the one hand and with little technical effort on the other.
- Such an artificial intelligence only requires a specific definition phase and a specific learning phase (training phase) until it supplies sufficiently precise initial data for a correct determination of the amount of substance. After completion of this definition and learning phase, this artificial intelligence is suitable as a software-based, in particular algorithm-based model, to be used as a technical model and thus as a replacement for a technically complex and correspondingly cost-intensive sensor system in commercial vehicles.
- an expensive sensor system for determining an emitted nitrogen oxide concentration (NOx) can be avoided.
- the amount of the emitted substance can be determined in a technically simple and cost-effective manner.
- the respective neural network or model is learned, preferably with the help of signals that are already available on the commercial vehicle.
- the data processing device or its at least one neural network can then be used as a trained, virtual sensor system in order to determine the amount of substance in question in a technically reliable and cost-effective manner.
- further transfer data are transferred to the register, namely the signals already mentioned which are generated independently of the amount of substance.
- These signals or data are preferably transferred - possibly in a further processed form - into a storage unit of the register that is separate from the storage unit of the output data. Saving this data in the distributed register enables access to this data if required and with the appropriate authorization. For example, the plausibility of the emitted amount of substance can be verified with little technical effort on the basis of these stored signals or input data.
- basic data - process data can also be generated, which assigns individual basic data and is also transferred as transfer data to a storage unit of the register.
- process data can contain, for example, a proof of origin of the basic data and / or a time stamp of the basic data.
- the process data are preferably transferred to the corresponding memory unit of the register together with the respective basic data. The process data can thereby ensure the authenticity of the Support basic data. Checking the authenticity of the basic data is even easier in terms of data technology.
- Transfer data are preferably stored unchangeably in a corresponding memory unit of the register.
- the transfer data can contain the aforementioned basic data and / or process data. This supports a tamper-proof provision of the data content of the respective storage unit.
- the manipulation security of the transfer data to be stored in the register is further supported in that these data are preferably stored in encrypted form. Strong encryption can take place, for example, in the form of hash-protected data blocks.
- the output data representing the amount of substance emitted are preferably encrypted in a processing stage downstream of the data processing device before they are transferred to the register as encrypted data.
- the processing stage can be arranged on the utility vehicle or within the sphere of influence of the manufacturer of the functional unit or the utility vehicle.
- the processing stage has a suitable digital key for the encryption.
- the processing stage preferably has a digital certificate which entitles it to participate in the register or the data network.
- the signals generated independently of the amount of substance can be encrypted in a control unit, which is preferably located on the utility vehicle.
- the control unit has a suitable digital key for the encryption on.
- this control unit preferably has a digital certificate which authorizes it to participate in the register or the data network.
- the encrypted data are preferably transferred to the register by means of one (or more) suitable data interfaces (gateways).
- suitable data interfaces e.g. signals generated independently of the amount of substance emitted, output data, process data
- the technical effort required to provide a suitable interface can be kept correspondingly low.
- the handling of the distributed register is preferably regulated in such a way that, depending on an authorization for (read) access, the data content of individual or all storage unit (s) or a copy of this data content can be accessed.
- This allows an authorized third party, for example the manufacturer or user of the functional unit or an institution (e.g. TÜV, testing authority) to check the functioning of the functional unit with little technical effort, be it for example on a random basis or over a defined working period of the functional unit.
- the access authorization restricts the group of people to officially authorized persons who are allowed to connect to the register, which functions as a private network. Access to the respective data content or to a copy of this data content by authorized persons can take place by means of a data network (e.g. Internet).
- a data network e.g. Internet
- Blockchain technology is preferably used to carry out the method.
- desired properties such as authenticity or protection against manipulation of the stored data can be implemented particularly reliably.
- it is a private data network (private blockchain) with an authorized group of participants that is restricted and authorized by means of suitable access regulations. Individual participants can also have different data transfer and / or data access authorizations with regard to the volume of data.
- the technology under the term blockchain is well known (e.g. Blockchain for dummies, Manav Gupta, 2017, ISBN: 978-1-119-37123-6).
- Preferred substances examined with regard to their emitted substance quantity are various nitrogen oxides NOx such as NO and N02, carbon dioxide (C02), carbon monoxide (CO), hydrocarbons (CmHn). These substances are relevant, for example, when operating an internal combustion engine as a functional unit.
- NH4 ammonium
- N03 nitrate
- P205 phosphate
- K20 potassium
- nitrate concentration in the ground eg in a field or meadow
- the amount of nitrate or nitrate concentration is emitted indirectly through the application of liquid manure or nitrogen into the soil and subsequent conversion in the soil.
- the method can be applied to different functional units which emit an amount of substance to be examined or determined.
- an internal combustion engine or an exhaust gas aftertreatment system of the commercial vehicle are conceivable as a functional unit.
- add-on devices or sub-units thereof are also conceivable as a functional unit of the utility vehicle, since they perform a function when the utility vehicle is used for work.
- this is a filling or application device (e.g. nozzle, valve, line) for liquid manure, preferably on a liquid manure trailer.
- a technically complex and correspondingly costly sensor system and measuring device can be avoided.
- Signals from the respective signal source preferably represent one or more parameters of the functional unit.
- a current state or actual state of the functional unit with respect to a parameter is mapped with the signals.
- the data processing device can thus continuously take into account a current state of the functional unit.
- the parameter signals are independent of a direct determination of the amount of substance and at the same time are related to the current state and current properties of the functional unit.
- these are In many cases, parameters are routinely available on the commercial vehicle, in particular through conventional sensors. Thus the technical effort for the provision of substance-independent gene-independent signals for determining the substance amount remains low.
- Suitable signals as input data for the data processing device are, for example, parameter values of at least one of the following parameters: an exhaust gas temperature of the combustion gases of an internal combustion engine of the commercial vehicle, a torque of the internal combustion engine, a speed of the internal combustion engine. Further parameters can be ambient conditions (e.g. temperature, external air pressure) of the functional unit or other technical parameters on the functional unit.
- the aforementioned parameters are particularly suitable as a functional unit in the case of an internal combustion engine or an exhaust gas aftertreatment system.
- parameters influencing the manure composition e.g. the species of animal, the feed of the animals, type and / or duration of the storage of the manure
- parameters influencing the manure composition e.g. the species of animal, the feed of the animals, type and / or duration of the storage of the manure
- Input data are preferably sent to the data processing device as a function of a comparison between signals from a signal source and at least one predefined reference value. This makes it possible for input data to be sent only as a function of a specific comparison result. A suitable comparison can therefore ensure that an investigated amount of substance is not determined continuously, but only under specifically determined conditions, namely only when the determination appears necessary. This advantageously reduces the number of data transactions and the computing capacity required. Depending on the data transmission medium used, this reduction also saves costs.
- the predefined reference value acts as a calibration value which represents a calibration state of the functional unit. This calibration state can then be compared with a current actual state of the function unit, which is represented by signals from the signal source.
- the calibration status of an internal combustion engine is predefined by reference values, in particular maximum values not to be exceeded, which were obtained in a test phase or during homologation of the internal combustion engine. These reference values relate, for example, to a maximum torque of the internal combustion engine, a maximum speed of the internal combustion engine or a maximum exhaust gas temperature of the combustion gases of the engine. A comparison between the calibration status and the actual status is therefore suitable as a preliminary test for an efficient decision as to whether an emitted amount of substance needs to be determined at all.
- input data are only sent to the data processing device if the value of the signal from the signal source (e.g. a measured torque of the internal combustion engine) is greater than the predefined reference value (e.g. a maximum torque specified during the homologation of the internal combustion engine).
- the predefined reference value e.g. a maximum torque specified during the homologation of the internal combustion engine.
- the method is preferably used to check the amount of substance emitted to determine whether it complies with a predetermined limit value.
- a predetermined limit value can be, for example, a maximum value stipulated by the manufacturer of the functional unit or by a legislator, which must be complied with or which must not be exceeded.
- the output data of the data processing device can, for example, be fed to a corresponding comparison algorithm in the already mentioned downstream processing stage. In the event that the processing stage is assigned to the sphere of influence of the manufacturer of the functional unit, the latter can easily check compliance with the limit value in a technically simple manner. By accessing the register or the data / data transactions stored there, authorized persons can check whether the emitted amount of substance complies with a predetermined limit value, even without the processing stage.
- FIG. 1 shows a first embodiment of a schematically illustrated arrangement for performing the inventive method
- FIG. 2 shows a further exemplary embodiment of a schematically illustrated arrangement for carrying out the method according to the invention
- FIG. 3 shows a further exemplary embodiment of a schematically illustrated arrangement for carrying out the method according to the invention.
- FIG. 4 shows the arrangement according to FIG. 1 combined with a schematically illustrated data architecture for carrying out the method according to the invention.
- FIG. 1 shows an arrangement 10 with several components for determining an amount of substance Em, which is emitted by the operation of a functional unit 12, 14 of a utility vehicle 15, in particular a tractor.
- the functional unit 12 is an internal combustion engine of the commercial vehicle, while the embodiment according to FIG.
- the functional unit 14 is designed as an application device for liquid manure provided only schematically.
- This application device 14 is part of a slurry trailer 16, which is pulled by the utility vehicle 15 in operation.
- the arrangement 10 can be designed partially or completely as part of the utility vehicle 15.
- a sensor system 18 detects current values of parameters of the internal combustion engine 12, for example an exhaust gas temperature T, a torque M and an engine speed of the Internal combustion engine 12.
- the sensor signals S_sen generated independently of the amount of substance Em to be determined by means of the sensor system 18 are fed to a control unit 20.
- the control unit 20 preferably contains the functionalities required for signal or data processing, such as read and / or write unit, memory unit, processor.
- signals or data from a data and / or control bus 22 are also fed to the control unit 20.
- This bus 22 is preferably present on the vehicle, for example a CAN bus.
- the control unit 20 sends received signals or data from the sensor system 18 and the bus 22, possibly in a processed form as input data D_in, to an input 24 of a data processing device 26.
- the sensor signals S_sen can also be sent directly to the data processing device 26 without the interposition of the control unit 20.
- the data processing device 26 contains at least one neural network NN, which is designed as a learned, software-based model for processing the input data D_ein.
- the at least one neural network NN forms, so to speak, a virtual sensor system, which replaces a direct measurement of the emitted amount of substance Em.
- output data D_aus are generated using the at least one neural network NN, which are at an output 28 of the Data processing device 26 are present and represent the emitted amount of substance Em.
- the output data D_aus are fed to a processing stage 30 in which the output data D_aus are compared, if necessary, in a further processed data form with a predetermined limit value W_gr.
- the comparison is used to check whether with the value of the output data D_aus - and consequently with the value of the arithmetically determined amount of substance Em - the predetermined limit value W_gr is complied with, in particular not exceeded.
- information that is dependent on the comparison result can also be generated and output for users of the functional unit 12 or for third parties. Furthermore, measures can be initiated in the processing stage 30, for example by outputting appropriate control signals.
- the data processing device 26 is preferably arranged outside of the utility vehicle 15 and in the area of influence of the manufacturer who produces the functional unit 12 and / or the utility vehicle 15.
- the processing stage 30 is preferably also arranged outside of the commercial vehicle 15 and in the area of influence of the manufacturer who produces the functional unit 12 and / or the commercial vehicle 15.
- the arrangement according to FIG. 2 differs from the embodiment according to FIG. 1 essentially in that in the control unit 20 signals S_sen of the sensor system 18 are compared with a predefined reference value W_ref during a comparison step S1.
- Input data D_ein are in Sent to the data processing device 26 as a function of the comparison result in the comparison step S1.
- the reference value W_ref corresponds to a calibration value W_kal, which represents a calibration state of the internal combustion engine 12.
- the calibration state has been defined by means of a test phase or homologation of the internal combustion engine 12.
- a permissible working range for the internal combustion engine 12 has been defined here.
- the calibration value W_kal therefore corresponds, for example, to a maximum permissible exhaust gas temperature T_max, a maximum permissible torque M_max or a maximum permissible speed n_max of the internal combustion engine 12.
- Signals S_sen of the sensor system 18 represent a recorded actual state of the internal combustion engine 12, since the sensor system 18 records current values of individual parameters of the internal combustion engine 12, e.g. the current exhaust gas temperature T, the current torque M and / or the current engine speed n.
- the arrangement 10 determines an emitted amount of substance Em at least one of the substances NO, NO2, CO2, CO, CmHn. These substances are of interest in connection with the operation of the internal combustion engine 12.
- the arrangement 10 according to FIG. 3 determines an emitted amount of substance Em in connection with the spreading of liquid manure on an agricultural area.
- the amount of substance Em at least one of the substances ammonium (NH4), phosphate (P205), potassium (K20), nitrogen (N), nitrate (N03) is determined.
- signals are generated independently of the amount of substance Em to be determined and in the control unit 20 in a possibly processed form provided in order to then be sent to the data processing device 26 as input data D_in.
- the neural network NN is specifically trained to calculate or determine a substance (eg NH4, P205, K20, N, N03) emitted as a virtual sensor system with regard to the emitted quantity.
- the signals provided by the control unit 20 are based on sensor signals S_sen and / or on signals or data from a data network 32 (e.g. Internet).
- a data network 32 e.g. Internet
- the latter can be used, for example, for a farmer or user to transmit a variable G_g that influences the slurry composition as a parameter to the control unit 20.
- This variable G_g can also be transmitted automatically as data from a database or as sensor signals via the data network 32 to the control unit 20.
- variable G_g influencing the manure composition is preferably a species of animal that produces the manure, the feed of the animals or also the type and / or duration of the storage of the manure.
- the following parameters come into consideration, apart from the aforementioned variable (s) G_g: weather conditions, solar radiation, surface properties of the field in question 36.
- the values of these parameters are preferably detected by means of a suitable sensor system 18 '.
- This sensor system 18 ' contains at least one sensor and can at least partially form part of one or more unit (s) outside the operated one Commercial vehicle 15, for example satellite, drone, weather station. Their signals or data S_sen are then fed to control unit 20.
- the nitrate concentration in the ground 34 can also be determined as an emitted amount of substance Em.
- the amount or concentration of nitrate is emitted indirectly through the application of liquid manure or nitrogen into the soil 34 and subsequent conversion in the soil 34.
- the output data D_from the data processing device 26 representing the respective amount of substance Em emitted are in turn fed to a processing stage 30.
- a processing stage 30 With regard to the function of the processing stage 30 in FIG. 3, reference is made to the explanations relating to the embodiment according to FIG. 1.
- the arrangement 10 is combined with a data architecture 38.
- the arrangement 10 corresponds to the embodiment according to FIG. 1.
- other embodiments of the arrangement 10 can also be combined with the data architecture 38.
- the data architecture 38 is used to record or document the amount of substance Em emitted and to check it as required by authorized or authorized persons.
- the output data D_aus are transferred as transfer data TD into a memory unit S1 of a digitally distributed register 40.
- the signals S_sen are likewise transferred as transfer data TD into a memory unit S2 of the register 40.
- Process data D_pl and D_p2 are generated in parallel with the output data D_aus and signals S_sen, which together can be referred to as basic data.
- the process data D_pl are preferably generated in the processing stage 30, while the process data D_p2 are preferably generated in the control unit 20.
- the process data D_pl and D_p2 are assigned to the respective basic data and transferred as transfer data TD into the corresponding memory unit S1 or S2.
- All transfer data TD that is to say basic data S_sen, D_aus and process data D_pl, D_p2, are stored in register 40 in an unchangeable and encrypted manner.
- the processing stage 30 has a digital key krl and the control unit 20 has a digital key kr2.
- the encryption of the transfer data TD is indicated with the addition of brackets (krl) or (kr2).
- the processing stage 30 preferably contains an integrated interface for the transmission of transfer data TD to the memory unit S1.
- the storage unit 20 sends encrypted data S_sen (kr2) and D_p2 (kr2) first to a separate data interface 42.
- This data interface 42 enables access to a telecommunication connection (e.g. mobile radio) in order to provide technical data to the control unit 20 with the register 40 associate.
- the control unit 20 sends in parallel the signals S_sen as non-encrypted input data D_ein to the data processing device 26.
- the distributed register 40 forms a type of data network with a limited number of authorized participants or technical modules for data transactions and / or access to data transactions already recorded in the register 40.
- the two modules control unit 20 and processing stage 30 are each authorized for data transactions.
- the technical module 44 preferably only has the authorization for read access to the data content of the storage units S1, S2.
- the modules 20, 30, 44 preferably each have a corresponding digital certificate.
- the module 44 is assigned in particular to an authorized institution which has the task of checking the documentation of the emitted substance quantities Em contained in the register 40. A comparison with the predetermined limit value W_gr can also be carried out in the module 44. In this way, a neutral entity can reliably check whether the predetermined limit value W_gr is being adhered to.
- the module 44 accesses the register 40 and the recorded data content of the storage units S1, S2 by means of a data network 46 (e.g. Internet).
- a data network 46 e.g. Internet
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- General Health & Medical Sciences (AREA)
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- Data Mining & Analysis (AREA)
- Mechanical Engineering (AREA)
- Computer Hardware Design (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
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Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102020201283.0A DE102020201283A1 (de) | 2020-02-03 | 2020-02-03 | Verfahren zur Überprüfung einer emittierten Stoffmenge |
| PCT/EP2021/051180 WO2021156056A2 (de) | 2020-02-03 | 2021-01-20 | Verfahren zur überprüfung einer emittierten stoffmenge |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4100635A2 true EP4100635A2 (de) | 2022-12-14 |
Family
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP21701708.6A Withdrawn EP4100635A2 (de) | 2020-02-03 | 2021-01-20 | Verfahren zur überprüfung einer emittierten stoffmenge |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US20230341294A1 (de) |
| EP (1) | EP4100635A2 (de) |
| CN (1) | CN114729609A (de) |
| DE (1) | DE102020201283A1 (de) |
| WO (1) | WO2021156056A2 (de) |
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| DE102022002242A1 (de) | 2022-06-21 | 2023-12-21 | Mercedes-Benz Group AG | Virtueller Sensor und Verfahren zum Betrieb eines virtuellen Sensors |
Family Cites Families (19)
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| DE10111586A1 (de) * | 2001-03-10 | 2002-09-12 | Volkswagen Ag | Verfahren zum Betrieb von Brennkraftmaschinen |
| US6616569B2 (en) * | 2001-06-04 | 2003-09-09 | General Motors Corporation | Torque control system for a hybrid vehicle with an automatic transmission |
| US8437903B2 (en) * | 2004-11-26 | 2013-05-07 | Lysanda Limited | Vehicular diagnostic system |
| US7774111B2 (en) * | 2006-08-08 | 2010-08-10 | General Motors Llc | Method and system for providing vehicle emissions data to an authorized recipient |
| US8244381B2 (en) * | 2007-10-04 | 2012-08-14 | Freescale Semiconductor, Inc. | Microprocessor, system for controlling a device and apparatus |
| ITMO20070304A1 (it) * | 2007-10-05 | 2009-04-06 | Octo Telematics S R L | Sistema e metodo per il rilevamento delle emissioni inquinanti di veicoli stradali o simili |
| US20090300422A1 (en) * | 2008-05-30 | 2009-12-03 | Caterpillar Inc. | Analysis method and system using virtual sensors |
| FR2984557B1 (fr) * | 2011-12-20 | 2014-07-25 | IFP Energies Nouvelles | Systeme et procede de prediction des emissions de polluants d'un vehicule avec calculs simultanes de la cinetique chimique et des emissions |
| US9474042B1 (en) * | 2015-09-16 | 2016-10-18 | Ivani, LLC | Detecting location within a network |
| DE102016001367A1 (de) * | 2016-02-06 | 2017-08-10 | GM Global Technology Operations LLC (n. d. Gesetzen des Staates Delaware) | Verfahren und System zum Ansteuern eines Verbrennungsmotors und/oder einer Abgasnachbehandlungseinrichtung eines Fahrzeugs, Fahrzeug mit einem solchen System sowie Computerprogrammprodukt zum Durchführen eines solchen Verfahren und Steuerungs- und/oder Regelungsvorrichtung mit einem derartigen Computerprogrammprodukt |
| US20190073701A1 (en) * | 2017-09-06 | 2019-03-07 | Tesloop, Inc. | Vehicle valuation model based on vehicle telemetry |
| GB2566741A (en) * | 2017-09-26 | 2019-03-27 | Phm Associates Ltd | Integrity of data records |
| CA3082398A1 (en) * | 2017-11-09 | 2019-05-16 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for the industrial internet of things |
| CN109781934A (zh) * | 2017-11-13 | 2019-05-21 | 富士通株式会社 | 环境传感器检测数据的处理装置、处理方法、计算机可读存储介质、以及环境传感器系统 |
| CN107945090A (zh) * | 2017-11-30 | 2018-04-20 | 深圳市轱辘车联数据技术有限公司 | 基于区块链的车辆尾气数据分析方法、装置及服务器 |
| DE102018000378A1 (de) * | 2018-01-18 | 2019-07-18 | Audi Ag | Verwertung von Schadstoffen aus Verbrennungsmotoren |
| CA3089745C (en) * | 2018-01-25 | 2023-09-26 | Fortress Cyber Security, LLC | Secure storage of data and hashes via a distributed ledger system |
| US10291395B1 (en) * | 2018-01-25 | 2019-05-14 | Fortress Cyber Security, LLC | Secure storage of data via a distributed ledger system |
| US11415464B2 (en) * | 2018-04-10 | 2022-08-16 | Advancetrex Sensor Technologies Corp. | Infrared thermal monitoring system for industrial application |
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2020
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2021
- 2021-01-20 US US17/760,008 patent/US20230341294A1/en active Pending
- 2021-01-20 EP EP21701708.6A patent/EP4100635A2/de not_active Withdrawn
- 2021-01-20 WO PCT/EP2021/051180 patent/WO2021156056A2/de not_active Ceased
- 2021-01-20 CN CN202180006655.8A patent/CN114729609A/zh active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| CN114729609A (zh) | 2022-07-08 |
| WO2021156056A2 (de) | 2021-08-12 |
| DE102020201283A1 (de) | 2021-08-05 |
| WO2021156056A3 (de) | 2021-10-14 |
| US20230341294A1 (en) | 2023-10-26 |
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